کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8502499 | 1554049 | 2018 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Identification of S-nitrosylated proteins in postmortem pork muscle using modified biotin switch method coupled with isobaric tags
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
دانش تغذیه
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Identification of S-nitrosylated proteins in postmortem pork muscle using modified biotin switch method coupled with isobaric tags Identification of S-nitrosylated proteins in postmortem pork muscle using modified biotin switch method coupled with isobaric tags](/preview/png/8502499.png)
چکیده انگلیسی
The objective of this study was to identify the S-nitrosylated proteins in aging samples of pork longissimus thoracis muscle (aged 0 and 3 d) and to study the effects of exogenous S-nitrosoglutathione (GSNO, concentration at 10 and 100â¯Î¼M) treatments of aged 0 d sample. After validating modified biotin switch method, the samples were labeled with tandem mass tags (TMT126-129) for the LC-MS/MS analysis. A total of 366 peptides were identified to be S-nitrosylated corresponding to 339 proteins. Comparison of total intensity and individual S-nitrosylated sites between aging samples revealed that S-nitrosylation did occur in pork muscle during postmortem aging through possible pathways of denitrosylation and transnitrosylation. GSNO treatment groups showed a considerable number of potential cysteines could be modified with high thiol-reactivity. It was deduced that S-nitrosylation could be involved in the postmortem metabolic process possibly through the regulation of activity or function of glycolytic enzymes, calcium release, heat shock proteins, antioxidant enzymes and myofibrillar proteins.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Meat Science - Volume 145, November 2018, Pages 431-439
Journal: Meat Science - Volume 145, November 2018, Pages 431-439
نویسندگان
Rui Liu, Qingquan Fu, Steven Lonergan, Elisabeth Huff-Lonergan, Lujuan Xing, Lili Zhang, Yun Bai, Guanghong Zhou, Wangang Zhang,